Intelligent knowledge based systems in electrical power engineering

Intelligent knowledge based systems in electrical power engineering

Intelligent knowledge based systems in electrical power engineering by J. R. Mcdonald, G. M. Burt, J. S. Zielinski, and S. D. J. Mcarthur

Contents Of Intelligent Knowledge Systems

  • Part One
  • A General Overview of Intelligent Knowledge Based systems
  • An introduction to intelligent knowledge based systems Jerzy S Zielinski and Stephen D J McArthur
  • Computers and artificial intelligence
  • A short history
  • Current trends in applied AI
  • Definition and terminology of IKBSs
  • Definitions
  • Terminology
  • The architecture Of IKBSs
  • The implementation cycle of IKBSs
  • References
  • Intelligent knowledge based system development Jerzy S Zielinski and Stephen D J McArthur
  • Historical review
  • General information
  • IKBS tools
  • Applications of IKBSs
  • IKBS generations
  • IKBSs in technology
  • Opportunities and bottlenecks in IKBS development
  • Discussion of costs and benefits
  • References
  • Further reading
  • The Application of Intelligent Knowledge Based Systems in
  • Electrical Power Engineering
  • Comments on contemporary power systems and other engineering systems Jerzy S Zielinski
  • Main characteristics of electrical power systems
  • Problems in electrical power system operation
  • Computer applications in power systems
  • A short history
  • Some remarks on hardware and software IKBSs
  • Some remarks on the relationships between phenomena in power systems and other fields of engineering Conclusions
  • References
  • Forecasting and planning in power systems
  • U George Knight
  • Introduction
  • Planning tasks in the extension of power systems
  • Forecasting tasks in the extension of power systems
  • The evolution of techniques for system planning and forecasting
  • The characteristics of system planning and forecasting tasks in relation to IKBSs
  • Algorithmic, human and expert system capabilities
  • The characteristics of planning and forecasting tasks in relation to IKBSs
  • Frequency of study
  • Retention of expertise
  • Areas of research and development
  • Descriptions of some proposed and actual applications of IKBSs in generation expansion planning
  • A decision tree and IKBS model
  • A combined dynamic programming, IKBSs and fuzzy sets approach
  • Descriptions of some proposed and actual applications of IKBSs in transmission network
    planning
  • An IKBS for the preliminary design of power transmission networks
  • Development of an IKBS for long-term planning of power transmission networks
  • Descriptions of some proposed and actual applications of IKBSs in distribution network planning
  • EHV /HV substation location and HV network design
  • Connection of new customers
  • Descriptions of some proposed and actual IKBSs in power system analysis
  • Interactive load flow for power system planning
  • Support to load flow calculations
  • Support for transient stability studies
  • Demand forecasting
  • Trends and conclusions
  • References
  • Design of electrical plant and systems
  • Stefano Massucco
  • Introduction
  • General overview
  • Reasons for the application of IKBSs to design and planning
  • The state of the art in IKBS applications for the design of electrical plant and systems
  • Introduction
  • Applications to large systems
  • Applications to systems of limited dimensions
  • Applications to the design of specific subsystems or equipment
  • An IKBS application: electrical auxiliary system design in a power station
  • Problem formulation
  • The IKBS approach: building the knowledge base and design procedure
  • Conclusions
  • Acknowledgements
  • References
  • Intelligent knowledge based systems in condition monitoring Barclay Weir
  • Introduction
  • Types of electrical machines
  • Condition monitoring
  • IKBSs in condition monitoring
  • Applications
  • Some Successful applications
  • TURBOMAC
  • Gen AID
  • GEMS
  • TOGA
  • MOTORMON
  • Summary
  • References
  • Alarm processing
  • David J Young and James R McDonald
  • Introduction
  • The history of alarm processing
  • Message routing
  • Message prioritization
  • Advanced alarm-processing techniques
  • Review of previous work
  • The practical problems of alarm processing
  • Speed of operation
  • Limited scope of telemetry
  • Missing alarm messages
  • Unreliable time ordering of alarms
  • Arrival rate of alarms is not constant
  • Multiple simultaneous events
  • Development of an alarm-processing expert system
  • Setting initial target Identification of knowledge and data requirements for the IKBS
  • Identification of existing data and knowledge
  • Knowledge acquisition
  • Identification of approach and IKBS techniques
  • Identification of language or tools for IKBS construction
  • Knowledge base design
  • User interface design
  • IKBS construction – knowledge base and user interface
  • Prototyping
  • Testing
  • Installation and integration
  • A case study: APEX
  • Details of APEX construction
  • Example of APEX operation Performance
  • Conclusion
  • References
  • Event and fault diagnosis Graeme M Burt and James R McDonald
  • Introduction to the problem of fault diagnosis
  • Events
  • Reasons for fault diagnosis
  • Basis for diagnosis
  • Reasons for a fault diagnosis system
  • IKB -based fault diagnosis
  • Review of IKBSs for network fault diagnosis
  • The automatic system trouble analysis’ system
  • IKBSs based on AST A ideas
  • A distributed approach
    Fault diagnosis using object-oriented features
  • Localized fault diagnosis
  • Applications where SCADA data is lacking
  • A system suited to parallel implementation
  • A system for distribution feeders
  • CRAFT – customer restoration and fault testing
  • SEPT
  • An IKBS developed by Amantegui et al
  • Further comments]
  • The development of an IKBS for fault diagnosis:
  • RESPOND
  • Introduction
  • Structure of the diagnosis: its results
  • Structure of the diagnosis: its mechanics
  • An initial prototype: wait-and-see
  • Hypothesizer strategy
  • Hypothesizer gut reaction
  • Evolution of hypothesizing strategies for central diagnosis
  • Dealing with uncertainty
  • Network data requirements
  • Qualitative simulation
  • Modelling knowledge
  • Demonstration of the developed system
  • Case study
  • Hypothesizer diagnosis
  • Final remarks
  • References
  • Other applications in power system operation and control
  • Jerzy S Zielinski
  • Voltage/reactive power control
  • Emergency control and restoration
  • Real-time processing
  • The testing of equipment
  • Transformers
  • Protection relays
  • Substations
  • Management systems
  • Electrical and other industries
  • References
  • Future trends in intelligent systems in power systems
  • Alan Moyes
  • Introduction
  • The importance of knowledge
  • Knowledge acquisition
  • Model-based reasoning
  • Case-based reasoning
  • Data mining
  • Integrated solutions for complex problems
  • Control and monitoring architecture
  • Integrated IKBSs
  • Conclusions
  • References

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